Product features and task effects on experienced richness, control and engagement in voicemail browsing

A recent focus is on creating engaging user experiences with digital products and services such as voicemail. This study aims to design towards increased levels of engagement in voicemail browsing by using the ‘Richness, Control and Engagement’ (RC & E) framework. This framework explains the levels of engagement in terms of the levels of richness and control that are shaped by the features of a product and the user’s expertise. A product was developed that utilized gestures and sound to access digital voicemail contents. An experiment was conducted in which 28 participants interacted with the product while varying (1) the number of features of the user interface, (2) the amount of voicemail content and (3) the type of task. Results showed that the levels of engagement could be predicted according to the levels of richness and control experienced when a task-term was added to the framework. Implications of the refined RC & E framework for interaction design practice are discussed.     

基于品牌策略的新产品开发设计

本文通过对企业的品牌策略及其特征的分析,结合具体实例,从产品自身、系列产品和不同类产品形象的"家族"产品三个方面,提出了新产品开发设计如何与品牌策略融合,从而为企业降低新产品开发的风险,提高人们对品牌的认知度,提升企业整体文化形象提供了一种思维方法。     

无装饰特征探析

"无装饰"风格源自20世纪60年代的建筑行业的功能主义设计思潮。然而,现代的"无装饰"的风格并不是排斥或摈弃装饰,而是将装饰之"道"融入装饰之"器"。本文探讨无装饰自身的特征,使装饰的外延扩展。     

工装夹具增强装配技术研究应用

为了减少装配操作步骤和提高装配准确度和效率,在现有CAD软件装配功能的基础上提出一种基于装配特征识别的增强装配算法,利用特征识别以及定义的特征之间的装配关系实现增强装配功能,进而能实现装配的自动化。基于该算法实现的增强装配系统具有良好的扩充性,在实际装配应用中提高CAD软件装配功能的效率。     

基于ROI多特征和相关反馈的图像检索算法

本文提出了一种基于感兴趣区域(ROI)综合多特征和相关反馈的图像检索算法.在对图像进行四叉树分解的基础上,由用户选择感兴趣区域,综合颜色、纹理和形状三种底层特征进行多层感兴趣区域检索;由相关反馈技术体现用户感知的主观性,通过调整感兴趣区域、特征问、特征内的权重来提高查准率.给出了改进的CBIR通用模型和特征权重模型.实现了一个图像检索原型系统,将不同实验结果进行了比较和分析,实验结果表明,该文提出的方法具有良好的检索效果.     

语言学组合特征在语义关系抽取中的应用

语义关系抽取是信息抽取中的一个重要的研究领域。目前基于特征向量的语义关系抽取已经很难通过发掘新的特征来提高抽取的性能。本文提出了一种特征组合方法,通过在各种词法、语法、语义的基本特征内部及特征之间进行合理的组合形成组合特征,使用基于支持向量机的学习方法,使得关系抽取的准确率和召回率得到了提高。在ACE 2004语料库的7个关系大类和23个关系子类抽取实验中F值分别达到了66.6%和59.50%。实验结果表明通过对基本语言学特征进行组合所得到的组合特征能够显著地提高语义关系抽取的性能。     

图像处理技术在面包烘焙品质检验中的应用

阐速了数字图像处理技术在烘焙面包品质检验中的应用,依据灰度共现矩阵算法提取图像的纹理特征,并通过二值化后的烘焙面包切片计算出其体积。试验结果表明,该方法不仅为面包烘焙品质的快速自动检验提供了客观准确的科学依据,使感官评价的指标客观化,而且经济可行。     

A rationale for the TEI recommendations for feature-structure markup

In this paper, we concentrate on justifying the decisions we made in developing the TEI recommendations for feature structure markup. The first four sections of this paper present the justification for the recommended treatment of feature structures, of features and their values, and of combinations of features or values and of alternations and negations of features and their values. Section 5 departs briefly from the linguistic focus to argue that the markup scheme developed for feature structures is in fact a general-purpose mechanism that can be used for a wide range of applications. Section 6 describes an auxiliary document called a feature system declaration that is used to document and validate a system of feature-structure markup. The seventh and final section illustrates the use of the recommended markup scheme with two examples, lexical tagging and interlinear text analysis.Terry Langendoen is Professor and Head of the Department of Linguistics at The University of Arizona. He was Chair of the TEI Committee on Analysis and Interpretation. He received his PhD in Linguistics from the Massachusetts Institute of Technology in 1964, and held teaching positions at The Ohio State University and the City University of New York (Brooklyn College and the Graduate Center) before moving to Arizona in 1988. He is author, co-author, or co-editor of six books in linguistics, and of numerous articles.Gary Simons is Director of the Academic Computing Department of the Summer Institute of Linguistics, Dallas, TX. He served on the TEI Committee on Analysis and Interpretation. He received his PhD in Linguistics (with minor emphasis in Computer Science) from Cornell University in 1979. Before taking up his current position in 1984, he spent five years in the Solomon Islands doing field work with SIL. He is author, co-author, or co-editor of eight books in the fields of linguistics and linguistic computing.The initial feature-structure recommendations were formulated by the Analysis and Interpretation Committee at a meeting in Tucson, Arizona in March 1990, following suggestions by Mitch Marcus and Beatrice Santorini. The authors received valuable help in the further revision and refinement of the recommendations from Steven Zepp.     

基于多变量形态学特征的健康老年人认知发展预测算法

由于体积、表面积等常规形态学指标对于皮层下核团而言过于笼统,因此传统的形态特征获取手段难以检测到其表面形态的细微变化。为解决这一问题,本文提出了一种针对皮层下核团的精细特征提取算法,并将其应用到老年人认知状态预测任务上。通过表面共形参数化、表面共形表示和基于互信息的表面流配准,提取了46名被试双侧海马和杏仁核各15 000×2个顶点上的形态学特征;通过斑块选择、稀疏编码与字典学习,和最大池化的降维流程,避免了维度诅咒的同时充分保留了核团的纹理信息;最后,以树为弱学习器,采用GentleBoost算法集成了最终的强分类器做认知预测。结果显示,仅纳入海马和杏仁核两个皮层下结构的新颖特征,即可达到85%的预测准确率,为皮层下结构的精细特征发掘提供了新思路。     

Performance comparison of texture feature analysis methods using PNN classifier for segmentation and classification of brain CT images

A computer software system is designed for the segmentation and classification of benign and malignant tumor slices in brain computed tomography images. In this paper, we present a texture analysis methods to find and select the texture features of the tumor region of each slice to be segmented by support vector machine (SVM). The images considered for this study belongs to 208 benign and malignant tumor slices. The features are extracted and selected using Student's t‐test. The reduced optimal features are used to model and train the probabilistic neural network (PNN) classifier and the classification accuracy is evaluated using k fold cross validation method. The segmentation results are also compared with the experienced radiologist ground truth. Quantitative analysis between ground truth and segmented tumor is presented in terms of quantitative measure of segmentation accuracy and the overlap similarity measure of Jaccard index. The proposed system provides some newly found texture features have important contribution in segmenting and classifying benign and malignant tumor slices efficiently and accurately. The experimental results show that the proposed hybrid texture feature analysis method using Probabilistic Neural Network (PNN) based classifier is able to achieve high segmentation and classification accuracy effectiveness as measured by Jaccard index, sensitivity, and specificity.